Maintenance for Improving Manufacturing Equipments Availability Using Prognostics and Health Management

2011 ◽  
Vol 199-200 ◽  
pp. 543-547 ◽  
Author(s):  
Jiang Long ◽  
Wei An Jiang
Keyword(s):  
Health Monitoring ◽  
Health Management ◽  
Cost Effective ◽  
Prognostics And Health Management ◽  
Maintenance Strategy ◽  
Maintenance Strategies ◽  
Key Issues ◽  
Reliability And Availability

There is a growing need for improving manufacturing equipments availability to achieve high levels of productivity. As a key complement to CBM and RCM, PHM is becoming a key enabler for achieving cost effective ultra-reliability and availability in tomorrow’s manufacturing equipments at an affordable cost. Based on traditional maintenance strategies, key issues pertaining to PHM application to manufacturing equipments, including health monitoring, diagnostics and prognostics, are discussed in this paper. As an example, a method for dynamic MFOP based maintenance strategy optimization using PHM and RUL estimation is presented.

An Approach for Cost Effective Assessment in Risk-Based Maintenance as a Life-Cycle Maintenance (LCM) Model

2004 ◽  
Author(s):  
Masataka Yatomi ◽  
Akio Fuji ◽  
Noriko Saito ◽  
Toshiaki Yoshida
Keyword(s):  
Life Cycle ◽  
Power Plants ◽  
Cost Effective ◽  
Life Extension ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Original Design ◽  
Maintenance Strategies ◽  
Effective Assessment ◽  
Maintenance Plan

For aged power plants in Japan, the life extension with retaining the safety and cost-effective beyond the original design lifetime is proposed. Therefore it is important to minimise the risk and maintenance cost to keep operating the plants. Life-Cycle Maintenance (LCM) is proposed for optimising maintenance plan with reliability in the life of the plants. Risk Based Maintenance (RBM) is included in the LCM to assess the risk of components in the plants. LCC and the investment assessment may be also conducted to decide the most cost effective maintenance strategy, if several maintenance strategies are proposed in RBM. In this paper, concept and an application of the LCM are described to optimise maintenance plan in the lifetime of a plant. It was found that the LCM is quite useful method to plan the most cost effective maintenance strategies in the lifetime of the plant.

Analysis of Aircraft Composite Structural Health Monitoring and Life Prediction Technology

2011 ◽  
Vol 88-89 ◽  
pp. 515-523
Author(s):  
Xiao Chuang Tao ◽  
Chen Lu
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Life Prediction ◽  
Health Management ◽  
Structure Design ◽  
Prognostics And Health Management ◽  
Aircraft Structure ◽  
Reliability Design ◽  
Structural Health ◽  
Critical Issues

Along with the constantly updated aircraft structure design, higher performance and reliability design indexes as well as usage of a large portion of new materials especially lightweight composite materials put forward higher requirements for aircraft structure safety. The damage detection, diagnosis, forecast and management become an important part of aircraft Prognostics and Health Management(PHM).In order to better build the Structural Prognostics and Health Management system of a new generation aircraft for the improvement of security, task reliability and economy, this paper introduced the development situation of aircraft composite structural health monitoring and life prediction technologies, classified the existing technologies, and then discussed the principle, quality point, applicability and application situation, finally, pointed out several critical issues which still need further study.

scholarly journals Present Status and Future Growth of Advanced Maintenance Technology and Strategy in US Manufacturing

2020 ◽  
Vol 7 (3) ◽  
Author(s):  
Xiaoning Jin ◽  
Brian A. Weiss ◽  
David Siegel ◽  
Jay Lee
Keyword(s):  
Health Management ◽  
Manufacturing Firms ◽  
Future Trends ◽  
Prognostics And Health Management ◽  
Present Level ◽  
Maintenance Strategies ◽  
Manufacturing Enterprises ◽  
Specific Factors ◽  
The Impact ◽  
Future Growth

The goals of this paper are to 1) examine the current practices of diagnostics, prognostics, and maintenance employed by United States (U.S.) manufacturers to achieve productivity and quality targets and 2) to understand the present level of maintenance technologies and strategies that are being incorporated into these practices. A study is performed to contrast the impact of various industry-specific factors on the effectiveness and profitability of the implementation of prognostics and health management technologies, and maintenance strategies using both surveys and case studies on a sample of U.S. manufacturing firms ranging from small to mid-sized enterprises (SMEs) to large-sized manufacturing enterprises in various industries. The results obtained provide important insights on the different impacts of specific factors on the successful adoption of these technologies between SMEs and large manufacturing enterprises. The varying degrees of success with respect to current maintenance programs highlight the opportunity for larger manufacturers to improve maintenance practices and consider the use of advanced prognostics and health management (PHM) technology. This paper also provides the existing gaps, barriers, future trends, and roadmaps for manufacturing PHM technology and maintenance strategy.

scholarly journals Wind Turbine Prognostics and Health Management

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
David He ◽  
Eric Bechhoefer ◽  
Abhinav Saxena
Keyword(s):  
Health Management ◽  
Energy Systems ◽  
Electrical Energy ◽  
The United States ◽  
Offshore Wind ◽  
Prognostics And Health Management ◽  
Maintenance Strategy ◽  
Generating Capacity ◽  
The Cost ◽  
Installed Capacity

Wind power generating capacity was 239 GW at the end of 2011, with a further 46 GW of installed capacity to be operational by the end of 2012. While only providing 2.8% of the energy produce in the United States, its is anticipated that by 2030, fully 20% of the electrical energy will come from wind. This widespread deployment of industrial wind projects will require a more proactive maintenance strategy in order to be more cost competitive with traditional energy systems, such as natural gas or coal. This will be particularly true for offshore wind projects, where availability of the site for maintenance can be restricted for extend period of time due to weather. Prognostics and Health Management of these assets can improve operational availability while reducing the cost of unscheduled maintenance.

scholarly journals Measurement and Evaluation for Prognostics and Health Management (PHM) for Manufacturing Operations – Summary of an Interactive Workshop Highlighting PHM Trends

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Brian Weiss ◽  
Michael Brundage
Keyword(s):  
Health Management ◽  
Cost Effective ◽  
Lessons Learned ◽  
Annual Conference ◽  
Prognostics And Health Management ◽  
Manufacturing Operations ◽  
Current State ◽  
Effective Manner ◽  
Measurement And Evaluation ◽  
Interactive Workshop

Personnel from the National Institute of Standards and Technology (NIST) organized and led a Measurement and Evaluation for Prognostics and Health Management for Manufacturing Operations (ME4PHM) workshop at the 2019 Annual Conference of the Prognostics and Health Management Society held on September 23rd, 2019 in Scottsdale, Arizona. This event featured panel presentations and discussions from industry, government, and academic participants who are focused in advancing monitoring, diagnostic, and prognostic (collectively known as prognostic and health management (PHM)) capabilities within manufacturing operations. The participants represented a diverse cross-section of technology developers, integrators, end-users/manufacturers (from small to large), and researchers. These contributors discussed 1) what works well, 2) common challenges that need to be addressed, 3) where the community’s priorities should be focused, and 4) how PHM technological adoption can be sped in a cost-effective manner. This report summarizes the workshop and offers lessons learned regarding the current state of PHM. Based upon the discussions, recommended next steps to advance this technological domain are also presented.

Excitation Design for Damage Detection Using Iterative Adjoint-Based Optimization

2008 ◽  
Author(s):  
Matthew T. Bement ◽  
Thomas R. Bewley
Keyword(s):  
Structural Health Monitoring ◽  
Dynamic Response ◽  
Damage Detection ◽  
Health Monitoring ◽  
Cost Effective ◽  
Condition Based Maintenance ◽  
Maintenance Strategy ◽  
Engineering Applications ◽  
Effective Condition ◽  
Ambient Excitation

This paper presents a method for designing excitations for the purpose of enhancing the detectability of damage. The field of structural health monitoring (SHM) seeks to assess the integrity of structures for the primary purpose of moving from time-based maintenance to a more cost effective condition-based maintenance strategy. Consequently, most approaches to SHM are nondestructive in nature. One common nondestructive approach is known as vibration-based SHM. In this approach, a structure is instrumented with an array of sensors at various locations. The structure is then excited and its dynamic response recorded. This response is then interrogated to extract features that are correlated with damage. A survey of the SHM literature [1], [2], reveals that a great deal of attention has been paid to the data interrogation portion of the SHM process, with almost no attention paid to the excitation design. This focus is quite understandable in many applications where only ambient excitation is available, such as most civil engineering applications. However there are many applications where the excitation is selectable (e.g., most wave propogation approaches to SHM), and, indeed, where proper excitation selection is essential. As a simple example, consider a beam or column with a crack that is nominally closed due to a preload. If the provided excitation is not sufficient to open and close the crack, the detectability of the crack in the measured output will be severely limited.

scholarly journals A Framework for System Design Optimization Based on Maintenance Scheduling With Prognostics and Health Management

2013 ◽  
Author(s):  
Bo Yang Yu ◽  
Tomonori Honda ◽  
Syed Zubair ◽  
Mostafa H. Sharqawy ◽  
Maria C. Yang
Keyword(s):  
Health Management ◽  
Operating Conditions ◽  
Maintenance Scheduling ◽  
Prognostics And Health Management ◽  
Maintenance Strategies ◽  
Design Component ◽  
Trade Offs ◽  
Design Variables ◽  
System Design Optimization ◽  
High Level

The optimal maintenance scheduling of systems with degrading components is highly coupled with the design of the system and various uncertainties associated with the system, including the operating conditions, the interaction of different degradation profiles of various system components, and the ability to measure and predict degradation using prognostics and health management (PHM) technologies. Due to this complexity, designers need to understand the correlations and feedback between the design variables and lifecycle parameters to make optimal decisions. A framework is proposed for the high level integration of design, component degradation, and maintenance decisions. The framework includes constructing screening models for rapid design evaluation, defining a multi-objective robust optimization problem, and using sensitivity studies to compare trade-offs between different design and maintenance strategies. A case example of power plant condenser is used to illustrate the proposed framework and advise how designers can make informed comparisons between different design concepts and maintenance strategies under highly uncertain lifecycle conditions.

A Prognostics and Health Management (PHM) System for Electromechanical Braking (EMB) Systems in Trains

2021 ◽  
Author(s):  
Jingjing Weng ◽  
Chun Tian ◽  
Mengling Wu ◽  
Tianhe Ma
Keyword(s):  
Failure Modes ◽  
Health Management ◽  
Health Indicators ◽  
Prognostics And Health Management ◽  
Vehicle Operation ◽  
Battery Capacity ◽  
Battery State Of Charge ◽  
Key Issues ◽  
Sensor Signals ◽  
Mechanical Crack

Abstract Electromechanical brake (EMB) is a novel braking mode for railway trains. The reliability of the braking system is important for railway system safety. According to the RAMS (Reliability, Availability, Maintainability and Safety) requirements for railway applications, the key issues of prognostics and health management (PHM) for EMB systems are discussed at first. Consequently, the dominant tasks of the PHM system are confirmed, containing the battery State-of-Charge (SOC) and State-of-Health (SOH) estimation, electric components condition monitor, and mechanical crack prediction. Then the critical failure modes of the EMB system and their failure mechanisms are analyzed. Based on the above analysis, a PHM system developed for EMB systems and its working flow are introduced. The vehicle operation parameters, the brake control commands, and the sensor signals are inputs of the PHM system. These inputs are processed and gathered as health indicators. Then the PHM system adopts the physical model or the hybrid algorithms to track the failure mode and components. Finally, the PHM system locates the health stage of the EMB system. The primary health indicators for EMB systems are the braking distance and emergency battery capacity. And the health indicators for components are mapped with the corresponding failure modes. The estimation for the battery SOC and SOH is established based on the test results of battery properties. The model-based and data-driven hybrid method is utilized to detect the crack growth of mechanical components and the degradation in electric properties. The PHM system is useful for condition-based maintenance. And it is meaningful for the reliability and safety improvement of the EMB systems.

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